> For the complete documentation index, see [llms.txt](https://docs.myrspoven.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.myrspoven.com/getting-started/readme.md).
# Myrspoven
myCoreAI is Myrspoven's optimization layer for commercial and residential buildings. It connects to an existing Building Management System (BMS) and trains a physics-informed digital twin of how the building responds to weather, how it is used, and the control actions applied to it. From that, it automatically adjusts a selected set of control signals to cut energy waste while keeping indoor conditions inside agreed comfort bounds.
The building's existing HVAC logic stays in place — myCoreAI makes no permanent changes to it. Instead, it works on top of that logic, continuously tuning the relevant signals so the building runs at a more efficient operating point.
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### Audience
* **Portfolio and asset managers** use myCoreAI to reduce energy costs and improve operating margins across their building portfolio. myCoreAI connects to existing building systems and optimizes HVAC setpoints continuously — delivering measurable savings without capital expenditure or changes to existing infrastructure. It also supports energy management obligations under ISO 50001 and EPBD reporting.
* **Property and facility managers** are the day-to-day operators. They set comfort bounds, review performance, and respond to alerts — myCoreAI handles the continuous optimization in the background, so facility teams aren't manually tuning setpoints across the building.
* **System integrators and energy data providers** connect buildings to the platform by mapping existing BMS signals: the sensors myCoreAI reads and the setpoints it controls.\
Integration is signal-based and vendor-agnostic — stacks such as Schneider, Siemens, Honeywell, and Fidelix are fully supported.
* **Developers** work with Myrspoven via the Myrspoven AI-API to read signals, push setpoints, or build tooling on top of the platform. You can operate against the API directly or wire your own scripts and pipelines to it.
### How it works
Every hour, myCoreAI runs the same loop:
1. **Read** the latest signals from the BMS. This covers live sensor data — indoor temperatures, energy meters, equipment status — alongside the building's own configuration, such as current setpoints and system structure.
2. **Predict** how the building will respond over the next 72 hours, using the digital twin together with the weather forecast and learned patterns of how the building behaves.
3. **Optimize** the setpoint policy to minimize energy use while staying inside comfort bounds.
4. **Write** the resulting setpoints back to the BMS — pushed every 15 minutes.
The digital twin is retrained as new data arrives, so myCoreAI adapts as the building, weather, and usage patterns shift.
The myCoreAI control loop — sensors in, optimized setpoints out.
#### Worked example
Consider an office building heated by district heating on a capacity-based tariff — one where the cost depends partly on the building's peak power draw, not just total energy used. It connects its BMS via a standard signal mapping: zone temperatures, supply and return on two heating circuits, the primary heat meter, and the outdoor sensor. myCoreAI trains a digital twin on the building's recent operating history, then takes over the heating-circuit supply setpoints. In the weeks that follow, it flattens the morning ramp by pre-heating earlier at lower supply temperatures, holds zone temperatures inside the configured comfort bounds, and clips the daily peak below the tariff threshold.
Result: lower delivered energy and a reduced capacity charge, with no change to BMS logic.
### Key concepts
* **BMS / BAS (Building Management System / Building Automation System)** — the existing controller stack in the building (Schneider, Siemens, Honeywell, Fidelix, and others) that myCoreAI reads from and writes setpoints to.
* **Signal** — a single named data stream from the building. It is the level at which everything is represented: the sensor data read in the loop above (a temperature sensor, an energy meter), a setpoint, and equipment status are each one signal. See the [Developer reference](/developer-reference/overview.md).
* **Setpoint** — a writable value sent back to the BMS (for example, a heating-circuit supply temperature). The BMS's own control loops act on the setpoint.
* **Digital twin** — the physics-informed model of a specific building, trained from its sensor history. myCoreAI uses it to predict how setpoint changes will affect indoor conditions and energy use.
* **Optimization horizon** — how far ahead myCoreAI looks when choosing setpoints. Currently 72 hours.
* **Baseline (energy)** — the reference energy profile a building is compared against in reporting, used to estimate savings. This is distinct from the building's *control* baseline — how its own systems would run without myCoreAI — and the two must not be conflated.
* **Comfort bounds** — the indoor-condition bounds (typically temperature) myCoreAI must stay within. Configured per building, sometimes learned from historical data.
* **Energy cap** — optional feature that limits the building's peak power draw. Relevant for capacity-based ("effekt") tariffs, where charges scale with peak power rather than total energy.
* **myLoadshift** — shifts consumption across the day in response to spot-market electricity prices (e.g. ENTSO-E day-ahead).
## Where to next
| Audience | Start here |
| ---------------------------------------- | ------------------------------------------------------------- |
| **Customers** using myPortal | [myPortal](/customer-interfaces/myportal.md) |
| **BMS integration partners** | [BMS integration](/integrations/overview/bms-integrations.md) |
| **Developers** building against the APIs | [Developer reference](/developer-reference/overview.md) |
| All **integration options** | [Integrations](/integrations/overview/bms-integrations.md) |
| **Security and compliance** | [trust.myrspoven.com](https://trust.myrspoven.com/) |
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